2 papers
cs.AI2026
Learning, Potential, and Retention: An Approach for Evaluating Adaptive AI-Enabled Medical Devices
Alexis Burgon, Berkman Sahiner, Nicholas A Petrick +2
This work addresses challenges in evaluating adaptive artificial intelligence (AI) models for medical devices, where iterative updates to both models and evaluation datasets compli…
cs.LG2023
Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens
Jean Feng, Adarsh Subbaswamy, Alexej Gossmann +7
After a machine learning (ML)-based system is deployed, monitoring its performance is important to ensure the safety and effectiveness of the algorithm over time. When an ML algori…